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Ford Motor said on Monday it will take a $19.5 billion writedown and is killing several electric-vehicle models, in the most dramatic example yet of the auto industry’s retreat from battery-powered models in response to the Trump administration’s policies and weakening EV demand. The Dearborn, Michigan-based company said it will stop making the F-150 Lightning in its electric vehicle form, but will pivot to producing an extended-range electric model, a version of a hybrid vehicle called an EREV, which uses a gas-powered generator to recharge the battery. The company is also scrapping a next-generation electric truck, codenamed the T3, as well as planned electric commercial vans. Instead, Ford said it will pivot hard into gas and hybrid models, and eventually hire thousands of workers, even though there will be some layoffs at a jointly owned Kentucky battery plant in the near term. The company expects its global mix of hybrids, extended-range EVs and pure EVs to reach 50% by 2030, from 17% today. Ford will spread out the writedown, taken primarily in the fourth quarter and continuing through next year and into 2027, the company said. About $8.5 billion is related to cancelling planned EV models. Around $6 billion is tied to the dissolution of a battery joint venture with South Koreas SK On, and $5 billion on what Ford called program-related expenses. The automaker also raised its 2025 guidance for adjusted earnings before taxes and interest, to about $7 billion, up from a previous range of $6 billion to $6.5 billion. Fords shift reflects the auto industrys response to waning demand for battery-powered models, after car companies plowed hundreds of billions of dollars into EV investments early this decade. The outlook for electrics dimmed significantly this year as U.S. President Donald Trumps policies yanked federal support for EVs and eased tailpipe-emissions rules, which could encourage carmakers to sell more gas-powered cars. U.S. sales of electric vehicles fell about 40% in November, following the September 30 expiration of a $7,500 consumer tax credit, which had been in place for more than 15 years to stoke demand. The Trump administration also included in the massive tax and spending bill that passed in July a freeze on fines that automakers pay for violating fuel-economy regulations. Rather than spending billions more on large EVs that now have no path to profitability, we are allocating that money into higher-returning areas, said Andrew Frick, head of Fords gas and electric-vehicle operations. The F-150 Lightning rolled off assembly lines starting in 2022 with much fanfare comedian Jimmy Fallon wrote a song about the truck. Ford increased production of the model to meet an influx of 200,000 orders, but sales havent kept pace. The company sold 25,583 Lightnings through November of this year, a 10% decrease from the prior-year period. The successor to the F-150 Lightning, the T3 truck, was supposed to be built ground-up for production at a new complex in Tennessee, and be a core part of Fords second-generation EV lineup. Ford is now replacing production of the EV pickup with new gas-powered trucks starting in 2029 at the Tennessee factory. Ford effectively killed the entirety of its announced second-generation of EV models with Mondays announcement. For its future EV lineup, the company is shifting focus to more affordable EV models, conceived by a so-called skunkworks team in California. The first model from that team is slated to be priced at about $30,000 and go on sale in 2027. This midsize EV truck is being built at Fords Louisville plant. (Corrects the location of the battery plant to Kentucky, not Tennessee, in paragraph 3) Nora Eckert
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E-Commerce
AI is quickly moving beyond rote tasks and into the realm of bigger-picture decisions that once relied only on human judgment. As companies treat AI as a thinking partner, the technology also introduces new risks. But the efficiency gains are hard to ignore, and companies are going head first into adoption. Its very much like a chief of staff or a senior adviser, says Stacy Spikes, CEO of cinema subscription service MoviePass. To Spikes, AI platforms are a second or third set of eyes, helping him approach vendors or handle tricky people-to-people situations. He says he treats AI as a sounding board, not a decider. Im not letting it make the decision for me, or letting it predetermine what I’m going to go in and do, but I’m having it give me a better understanding, he says. Spikess experience shows the tension companies face as they roll out early use cases. AI can help employees act quickly and with greater precision, but organizations are still weighing what works and what doesnt, where the guardrails should be, and how to prevent judgment from slipping into autopilot. Across industries, leaders are now testing the interplay between AI and human judgmentand developing the processes that let the two work together. AI as a strategic partner Spikes embeds AI into his executive workflow. He likens it to how large firms use management consultants to map scenarios and risks, as well as act as a sounding board. He uses AI to help with complex decisions across people dynamics, situational gray areas, and selecting external partners or service teams: It could, for example, offer advice on handling disagreements between colleagues or partners, or offer alternate perspectives that challenge someones initial point of view. I’m constantly having conversations with different AI tools, says Spikes. Ill give them information and have stand-up conversations with themalmost like a full research team, the way you would use McKinsey or PwC consultants. He says hell come to a fork in the road of decisions and uses AI to decide this pathway or that pathway. Hell run scenarios related to ambiguous judgment calls through multiple models to compare perspectives, before stepping in himself. He says no sensitive data is shared with LLMs; when hes working with his team or vendors, he often asks for ideas on handling challenging milestone situations, including when the company has set goals or KPIs and misses them. The AI doesnt replace his decision-making; rather, it simply gives him more insight with which to make a decision. He points to a recent case with a contractor he let go. The work ended in the first week of the month, but the contractor insisted on being paid for the full month. Spikes ran the scenario through two different AI models. One gave a firm, black-and-white answerprorate the work and move on. Another tool framed the issue more gently, emphasizing the persons past contributions. While Spikes ultimately held to his earlier decisionprorating the paymenthe says the AI conversations influenced the tone, leading him to approach the discussion with more empathy. He thanked the vendor for their earlier work but explained that prorating was necessary to maintain fairness across the team, especially since people talk, he pointed out. But had he not consulted AI, he may not have been nudged toward that balance. Asked whether AI changed the underlying decision, Spikes says no, but it influenced his tone. It made me a little bit kinder than I would have been. Supporting day-to-day decisions Elsewhere, companies are weaving AI into operational decisions to give employees clearer visibility and speed up decision making. Dave Glick, Walmarts senior vice president of enterprise business services, says corporate teams use an internal AI tool called the associate super agent. It works like a single front door: employees ask a question, and the system quietly hands it off to small, task-specific tools in the background. One use case is when employees want to understand what went wrong with a shipment or delivery. A shipment might arrive without a corresponding purchase order or end up at the wrong building; the AI system gathers data from multiple sources to piece together what likely happened. Many of these tasks are sort of detective work, Glick says. This purchase order showed up at the wrong building, or this shipment showed up and we dont have a purchase order for it. So, the AI pulls everything together and shows them what likely happened. Glick emphasized that the human remains in control and can override any conclusion the AI suggests. What used to require digging through multiple databases is now compressed into a much faster preliminary review, with the AI assembling the data before the employee makes the call. Ultimately, the value of AI comes down to its ability to find and assemble the right data; if the data isnt clean, AI cant meaningfully support a decision. Marne Martin, CEO of expense-management software firm Emburse, noted that AI works best when the decision is repeatable and the data feeding it is clean. If you have more than 3.5% of inaccurate or highly biased data in your model, you will not get to the accuracy that you can just trust AI, she says. Similarly, Infosys CTO Rafee Tarafdar says the IT services firm ties AI reliance to risk: the higher the stakes and the shakier their confidence in the model for a given use case, the more a human needs to step in. Is it risky to over-rely on AI? The efficiency gains from using AI are early wins, but researchers caution that exposure to AI can change how people act, prompting them to defer to either AIs judgment too much or default to more control-oriented responses. In an interview, University of Massachusetts Lowell associate professor of management José-Mauricio Galli Geleilate says his research shows that consulting AI turns your framing of the problem and how you see the problem, nudging leaders more towards control, like punitive or surveillance-oriented solutions. His co-author Beth Humberd, also an associate professor of management at UMass Lowell, describes the effect as a kind of psychological distancing: when managers turn to a machine instead of a colleague, you dont have the human cues that you would have in asking another person for their thoughts, she says, which make you pause and consider the person on the other side. Léonard Boussioux, an assistant professor of information systems at the University of Washingtons Foster School of Business, says his research shows people can quickly fall in line with AI because the models are really good at crafting sound arguments, and humans tend to trust anything that feels logical and well-articulated. To curb these effects, researchers say organizations need to build in frictionby forcing people to slow down, questioning the output, and bringing in human context that AI cant capture. Companies say theyre using I to augment but not replace human judgment. And as adoption grows, many are still figuring out where the handoff will be. For many, the hurdle may be more cultural than technical: forcing employees to question AIs output, while getting comfortable with its integration into daily workflows. AI is a level up from where we normally are, says Spikes. A CEO now has another counselor that is limitless in its ability to pull in data and information. it’s informing me, and it’s giving me a wider point of view.
Category:
E-Commerce
LinkedIn is often seen as the purview of recruiters and thought leaders. But the professional networking platform is quietly attracting a rather unexpected audience. According to recent data, 18- to 24-year-olds now make up 20.5% of its user base. That tracks, as college students and recent grads enter a cutthroat job market, eager to build a personal brand and online résumé that might help them stand out from the competition. Whats more surprising is that high schoolers are also getting in on the game younger than ever, treating the platform as a means to get ahead. High school students are discussing how having a professional online presence before even beginning a career is simply showing initiative. Sharing volunteer work, internships, and professional goals where future employers can see them (and keeping brainrot slang content on TikTok) shows ambition, some argue. The pressure to hit 500 connections is real. LinkedIn opened its doors to users 13 and up back in 2013, long before todays teens were even online. But Gen Z and Gen Alpha are coming of age in a world where career anxiety starts early, as social media feeds them an endless scroll of entrepreneurs, side hustlers, and monetizable passions complete with six-figure salaries, however unrealistic it may be. As a result, early signs have shown that Gen Z and Gen Alpha may have stronger entrepreneurial aspirations than previous generations. A new survey of 2,002 Gen Z and Gen Alpha users (ages 12 to 28) by social commerce platform Whop found that more than half are already using the internet to earn money through digital side hustles like selling vintage clothing, streaming video games, and posting on social media. And its paying off. Gen Alpha members report making an average of $13.92 per hour from digital pursuits, well above the federal minimum wage. When teens are bringing in the equivalent of a $28,000 salary before they can drive, its no wonder they want a professional profile to match. For some teens, the platform acts as a great equalizer. LinkedIn can connect students, especially those who dont come from wealthy or well-networked backgrounds, to mentors, internships, and career paths they might not otherwise be aware of. Tools like LinkedIn Learning offer free courses in leadership, coding, design, and more. Yet, comparison culture is rampant across social media. And LinkedIn is no exception. The pressure of worrying about future careers is taking grip younger and younger. As the World Economic Forum’s The Future of Jobs and Skills report estimated back in 2016, 65% of children entering primary school that year will likely work in roles that didnt even exist yet. The same will most likely be true another decade from now. If you dont even know what job youll be applying for when you graduate, theres really no use worrying too much about it. After all, you only are 15 once.
Category:
E-Commerce
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